How are you separating the efficiency of the architecture from the efficiency of the substrate? Unless you have a brain made of transistors or an LLM made of neurons how can you identify the source of the inefficiency?
I believe human and machine learning unify into a pretty straightforward model and this shows that what we're doing that ML doesn't can be copied across, and I don't think the substrate is that significant.